Field of the Invention
The invention relates to an image processing method and an image processing system, and particularly relates to a depth image processing method and a depth image processing system.
Description of Related Art
In recent years, along with improvement of user experience requirements, a depth image technique becomes popular. A method for calculating a depth image includes using a structured light, a time of flight (TOF) method, a stereo matching method, etc. The stereo matching method is to take one of a left image and a right image as a reference, and look for an offset in another image. For example, a frame of a height of the left image is taken as a reference, the frame of the same height in the right image is shifted by one pixel each time from the leftmost to the rightmost to compare images in the frames one-by-one, so as to find the features with the highest similarity from the comparison results to obtain the offset of the left image frame and the right image frame, and then calculate a depth image according to the offset of the image frames.
Since the aforementioned method is required to move the frame from the leftmost of the image to the rightmost, hundreds or thousands of computations have to be performed in order to obtain one offset, which leads to a poor efficiency. Therefore, a method of first down scaling an image resolution and then calculating depth is provided, for example, an image resolution of 800*600 is first down scaled to 400*300 and then a depth value is calculated. Although the above method may decrease a computation amount, it may increase an error of the offset of a far-distance object, and result in a fact that a depth value of the far-distance object in the depth image cannot be identified.
Moreover, in a digital camera, if a distance of the captured object is too close, a disparity of the left image and the right image is large, such that the system has to spend more time to calculate a depth image, and a user has to wait for a long time on the depth image calculation, which decreases a user's experience. Therefore, it is a goal of effort for related technicians of the field to identify a depth value of the far-distance object under a premise of decreasing the computation amount of the depth value, and automatically determine not to calculate the depth image when the captured object is too close to decrease the waiting time of the user.